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Shaoguang Mao
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README.md
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[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
![version](https://img.shields.io/badge/version-1.0-blue)
bitnet.cpp is the official inference framework for 1-bit LLMs (e.g., BitNet b1.58). It offers a suite of optimized kernels, that support fast and lossless inference of 1.58-bit models on CPU (with NPU and GPU support coming next).
bitnet.cpp is the official inference framework for 1-bit LLMs (e.g., BitNet b1.58). It offers a suite of optimized kernels, that support **fast** and **lossless** inference of 1.58-bit models on CPU (with NPU and GPU support coming next).
The first release of bitnet.cpp is to support inference on CPUs. bitnet.cpp achieves speedups of **1.37x** to **5.07x** on ARM CPUs, with larger models experiencing greater performance gains. Additionally, it reduces energy consumption by **55.4%** to **70.0%**, further boosting overall efficiency. On x86 CPUs, speedups range from **2.37x** to **6.17x** with energy reductions between **71.9%** to **82.2%**. Furthermore, bitnet.cpp can run a 100B BitNet b1.58 model on a single CPU, achieving speeds comparable to human reading (5-7 tokens per second), significantly enhancing the potential for running LLMs on local devices. More details will be provided soon.
<img src="./assets/m2_performance.jpg" alt="m2_performance" width="800"/>
>The tested models are dummy setups used in a research context to demonstrate the inference performance of bitnet.cpp.
We hope the release of bitnet.cpp can inspire more 1-bit LLMs trained in large-scale settings.
## Demo
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## Supported Models
bitnet.cpp supports a list of 1-bit models available on [Hugging Face](https://huggingface.co/)
bitnet.cpp supports a list of 1-bit models available on [Hugging Face](https://huggingface.co/), which are trained with research settings.
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